• Computers and Concrete
• /
• v.27 no.2
• /
• pp.99-109
• /
• 2021

Experimental and discrete element methods were used to investigate the effects of echelon non-persistent joint on the failure behaviour of joint's bridge area under uniaxial compressive test. Concrete samples with dimension of 150 mm×100 mm×50 mm were prepared. Uniaxial compressive strength and tensile strength of concrete were 14 MPa and 1MPa, respectivly. Within the specimen, three echelon non-persistent notches were provided. These joints were distributed on the three diagonal plane. the angle of diagonal plane related to horizontal axis were 15°, 30° and 45°. The angle of joints related to diagonal plane were 30°, 45°, 60°. Totally, 9 different configuration systems were prepared for non-persistent joint. In these configurations, the length of joints were taken as 2 cm. Similar to those for joints configuration systems in the experimental tests, 9 models with different echelon non-persistent joint were prepared in numerical model. The axial load was applied to the model by rate of 0.05 mm/min. the results show that the failure process was mostly governed by both of the non-persistent joint angle and diagonal plane angle. The compressive strengths of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. It was shown that the shear behaviour of discontinuities is related to the number of the induced tensile cracks which are increased by increasing the joint angle. The strength of samples increase by increasing both of the joint angle and diagonal plane angle. The failure pattern and failure strength are similar in both methods i.e. the experimental testing and the numerical simulation methods.

• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.49-62
• /
• 2022

Experimental and discrete element methods were used to investigate the effects of triple joints lengths and triple joint angle on the failure behavior of rock mass under uniaxial compressive test. Concrete samples with dimension of 20 cm × 20 cm × 5 cm were prepared. Within the specimen, three imbedded joint were provided. The joint lengths were 2 cm, 4cm and 6 cm. In constant joint lengths, the angle between middle joint and other joints were 30°, 60°, 90°, 120° and 150°. Totally 15 different models were tested under compression test. The axial load rate on the model was 0.05 mm/min. Concurrent with experimental tests, the models containing triple joints, length and joint angle are similar to the experiments, were numerical by Particle flow code in two dimensions (PFC2D). Loading rate in numerical modelling was 0.05 mm/min. Tensile strength of material was 1 MPa. The results show that the failure behaviors of rock samples containing triple joints were governed by both of the angle and the length of the triple joints. The uniaxial compressive strengths (UCS) of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. Furthermore, it was shown that the compressive behavior of discontinuities is related to the number of the induced tensile cracks which are increased by decreasing the joint length. Along with the damage failure of the samples, the acoustic emission (AE) activities are excited. There were only a few AE hits in the initial stage of loading, then AE hits rapidly grow before the applied stress reached its peak. In addition, every stress drop was accompanied by a large number of AE hits. Finally, the failure pattern and failure strength are similar in both methods i.e., the experimental testing and the numerical simulation methods.

• Advances in concrete construction
• /
• v.14 no.5
• /
• pp.317-330
• /
• 2022

This paper investigated computationally and experimentally the interaction here between a notch as well as a micropore under uniaxial compression. Brazilian tensile strength, uniaxial tensile strength, as well as biaxial tensile strength are used to calibrate PFC2d at first. Then, uniaxial compression test was conducted which they included internal notch and micro pore. Experimental and numerical building of 9 models including notch and micro pore were conducted. Model dimensions of models are 10 cm × 10 cm × 5 cm. Joint length was 2 cm. Joints angles were 30°, 45° and 60°. The position of micro pore for all joint angles was 2cm upper than top of the joint, 2 cm upper than middle of joint and 2 cm upper than the joint lower tip, discreetly. The numerical model's dimensions were 5.4 cm × 10.8 cm. The fractures were 2 cm in length and had angularities of 30, 45, and 60 degrees. The pore had a diameter of 1 cm and was located at the top of the notch, 2 cm above the top, 2 cm above the middle, and 2 cm above the bottom tip of the joint. The uniaxial compression strength of the model material was 10 MPa. The local damping ratio was 0.7. At 0.016 mm per second, it loaded. The results show that failure pattern affects uniaxial compressive strength whereas notch orientation and pore condition impact failure pattern. From the notch tips, a two-wing fracture spreads almost parallel to the usual load until it unites with the sample edge. Additionally, two wing fractures start at the hole. Both of these cracks join the sample edge and one of them joins the notch. The number of wing cracks increased as the joint angle rose. There aren't many AE effects in the early phases of loading, but they quickly build up until the applied stress reaches its maximum. Each stress decrease was also followed by several AE effects. By raising the joint angularities from 30° to 60°, uniaxial strength was reduced. The failure strengths in both the numerical simulation and the actual test are quite similar.

• The KIPS Transactions:PartB
• /
• v.9B no.4
• /
• pp.389-390
• /
• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.541-546
• /
• 2006

Data Mining is the process of finding hidden patterns inside a large data set. Cluster analysis has been used as a popular technique for data mining. It is a fundamental process of data analysis and it has been Playing an important role in solving many problems in pattern recognition and image processing. If fuzzy cluster analysis is to make a significant contribution to engineering applications, much more attention must be paid to fundamental decision on the number of clusters in data. It is related to cluster validity problem which is how well it has identified the structure that Is present in the data. In this paper, we design an adaptive data mining model using fuzzy performance measures. It discovers clusters through an unsupervised neural network model based on a fuzzy objective function and evaluates clustering results by a fuzzy performance measure. We also present the experimental results on newsgroup data. They show that the proposed model can be used as a document classifier.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.243-253
• /
• 2012

An opinion mining technique which was developed from document classification in area of data mining now becomes a common interest in domestic as well as international industries. The core of opinion mining is to decide precisely whether an opinion document is a positive or negative one. Although many related approaches have been previously proposed, a classification accuracy was not satisfiable enough to applying them in practical applications. A opinion documents written in Korean are not easy to determine a polarity automatically because they often include various and ungrammatical words in expressing subjective opinions. Proposed in this paper is a new approach of classification of opinion documents, which considers only a frequency of word patterns and excludes the grammatical factors as much as possible. In proposed method, we express a document into a bag of words and then apply a learning algorithm using a frequency of word patterns, and finally decide the polarity of the document using a score function. Additionally, we also present the experiment results for evaluating the accuracy of the proposed method.

• Journal of KIISE:Software and Applications
• /
• v.32 no.5
• /
• pp.416-427
• /
• 2005

Web navigation mining is a method of discovering Web navigation patterns by analyzing the Web access log data. However, it is admitted that the log data contains noisy information that leads to the incorrect recognition of user navigation path on the Web's hyperlink structure. As a result, previous Web navigation mining systems that exploited solely the log data have not shown good performance in discovering correct Web navigation patterns efficiently, mainly due to the complex pre-processing procedure. To resolve this problem, this paper proposes a technique of amalgamating the Web's hyperlink structure information with the Web access log data to discover navigation patterns correctly and efficiently. Our implemented Web navigation mining system called SPMiner produces a WebTree from the hyperlink structure of a Web site that is used trl eliminate the possible noises in the Web log data caused by the user's abnormal navigational activities. SPMiner remarkably reduces the pre-processing overhead by using the structure of the Web, and as a result, it could analyze the user's search patterns efficiently.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.6
• /
• pp.121-128
• /
• 2010

Spatial data mining has been developed to support spatial association knowledge between spatial features or its non-spatial attributes for an application areas. At the present time, a number of researchers attempt to the data mining techniques apply to the several analysis areas, for examples, civil engineering, environmental, agricultural areas. Despite the efforts that, until such time as not existed practical systems for the gCRMDMs. gCRMDMs is merged with very large spatial database and CRM information system. Also, it is discovery the association rule for the predictions of customer's shopping pattern informations in a huge database consisted with spatial and non-spatial dataset. For this goal, gCRMDMs need spatial data mining techniques. But, nowadays, in a most case not exist utilizable model for the gCRMDMs. Therefore, in this paper, we proposed a practical gCRMDMs model to support a customer, store, street, building and geographical suited to the trade area.

• Journal of Intelligence and Information Systems
• /
• v.11 no.3
• /
• pp.83-101
• /
• 2005

Customer retention is one of the major issues in life insurance industry, in which competition is increasingly fierce. There are many things for the life insurers to do many things to retain the customers. One of those things is to make sure to keep in touch with all customers. When an insurance-planner resigned, his/her customers must be taken care of by some planner-assistants. This article outlines the design of Contact Scheduling System (CSS) that supports planner-assistants for contacting the customers. Planner-assistants are unable to share the resigned insurance-planner's experience and knowledge regarding the customer relationship management. The CSS developed by employing both Classification And Regression Tree (CART) technique and Sequential Pattern Mining (SPM) technique has a two-stage process. In the first stage, it segments the customers into eight groups by CART model. Then it generates contact scheduling information consisting of contact-purpose, contact-interval and contact-channel, according to the segment's typical contact pattern. Contact-purpose is derived by schedule-driven, event-driven, or business-rule-driven. Schedule-driven contact is determined by SPM model. In the operation of CSS in a realistic situation, it shows a practicality in supporting planner-assistants to keep in touch with the customers efficiently and effectively.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.18 no.6
• /
• pp.1938-1944
• /
• 2004

In this study, when we make a diagnosis of constitution using QSCC Ⅱ(Questionnaire of Sasang Constitution Classification). data mining techniques are applied to seek the classification function for improving the accuracy. Data used in the analysis are the questionnaires of 1051 patients who had been treated in Dong Eui Oriental Medical Hospital and Kyung Hee Oriental Medical Hospital. The criteria for data cleansing are the response pattern in the opposite questionnaires and the positive proportion of specific questionnaires in each constitution. And the criteria for variable selection are the test of homogeneity in frequency analysis and the coefficients in the linear discriminant function. Discriminant analysis model and decision tree model are applied to seek the classification function into Sasang constitution. The accuracy in learning sample is similar in two models, the higher accuracy in test sample is obtained in discriminant analysis model.